Neo4j Staff Predictions for 2020
By Jocelyn Hoppa
January 8, 2020 6 mins read
A new year (let alone a new decade) is always a great time to reflect on the year gone past but also where we’re headed. We leaned on some of our most forward-thinking Neo4j colleagues – Amy Hodler, Michael Hunger… Read more →
Explore: ai • data science • data supply chain • GQL • graph algorithms • Graph Analytics • graph feature engineering • graph technology • machine learning • ML
The Top 7 Neo4j Videos of 2019
By Jessica Baumgardner
December 27, 2019 2 mins read
In lieu of our bi-weekly #GraphCast, we thought we would share some of the best Neo4j videos from 2019. Consider this an almost-New Year’s Eve celebration of all things video. (No order or favorites here. Just cool videos in a… Read more →
Explore: ai • artificial intelligence • data discovery • emil eifrem • GraphCast • Knowledge Graph • Lyft • machine learning • nasa • nodes
The Top 5 Neo4j Podcasts of 2019
By Bryce Merkl Sasaki
December 24, 2019 2 mins read
Catch up with all of the best episodes from the Neo4j Graphistania podcast during 2019, including episodes with the rebooted format and new co-host.
Explore: ai • data journalism • data science • graph algorithms • graph technology • Graphistania • information theory • machine learning • Neo4j Community • podcast
Graphs on GPUs: 5-Minute Interview with Saul Rosales
By David Penick
December 6, 2019 3 mins read
In this week’s five-minute interview (conducted at GraphTour DC 2019), we discuss how Saul Rosales and his team use Neo4j with Graphistry.
Explore: 5-minute interview • artificial intelligence • cybersecurity • data lakes • GPUs • graph database • graph technology • Graphistry • machine learning • Saul Rosales
Responsible AI: The Critical Need for Context (and Practical Tips)
By Jocelyn Hoppa
November 26, 2019 7 mins read
Read the second and final installment of this blog series on responisble AI, why context is critical to achieving responsible AI, and get practical tips.
Explore: ai and context • community detection • data lineage • data manipulation • fraud • graph algorithms • Graph Data • Graph Theory • healthcare data • machine learning
A Conversation with Graphs
By Corin Gainey
November 20, 2019 16 mins read
Editor’s Note: This presentation was given by Tatiana Hartinger at GraphConnect New York in September 2018. Presentation Summary Tatiana Hartinger is a mathematician and a Cognitive Solutions Consultant specializing in graph theory from Cognitiva. Cognitiva is using graphs to enhance… Read more →
Explore: ai • Connected Data • cypher • graph algorithms • Graph Databases • Graph Theory • graphconnect • json • machine learning • neo4j
Reveal Hidden Patterns In Healthcare Data: Graph Analytics and the Opioid Crisis
By Jocelyn Hoppa
November 19, 2019 8 mins read
Read this blog series to discover leading-edge graph analytic techniques to derive intelligence from complex healthcare data.
Explore: business intelligence • data scientists • graph algorithms • Graph Analytics • healthcare data • machine learning • neo4j • Neo4j Bloom • opioid crisis
Real Examples of Why We Need Context for Responsible AI
By Jocelyn Hoppa
November 12, 2019 8 mins read
Read part one of this two-part series on responsible AI. Discover real-world examples of the myths,., biases and more that currently surround AI.
Explore: ai myths • AI standards • artificial intelligence • biased ai • data scientists • inappropriate ai • machine learning • national institute for standards and tools • neo4j • NIST
How Boston Scientific Improves Manufacturing Quality Using Graph Analytics
By Corin Gainey
October 16, 2019 20 mins read
Editor’s Note: This presentation was given by Eric Wespi and Eric Spiegelberg at GraphConnect New York in September 2018. Presentation Summary We’re going to talk about some project themes that make sense when you’re going about developing a graph project.… Read more →
Explore: artificial intelligence • Connected Data • cypher • graph database • GraphAware Hume • graphconnect • Hume • machine learning • neo4j • nlp
Live from Lyft: Q&A with Mark Grover, Product Manager at Lyft
By Corin Gainey
September 26, 2019 5 mins read
Discover how Lyft has integrated Neo4j into their data sharing process and how they test information integrity with Amundsen.
Explore: Connected Data • data discovery • data model • Data Visualization • ETL tool • graph database • graph technology • Knowledge Graph • Lyft • machine learning
How Graphs Enhance Artificial Intelligence
By Jocelyn Hoppa
September 18, 2019 11 mins read
Explore the increasing impact of graph technology on artificial intelligence and the steps toward enhancing AI and ML with a graph database.
Explore: ai • artificial intelligence • feature engineering • graph embeddings • graphconnect • knowledge graphs • machine learning • ML • native learning • neural networks
DeepWalk: Implementing Graph Embeddings in Neo4j
By Jocelyn Hoppa
September 12, 2019 10 mins read
Discover tips and strategies for implementing graph embedding into a Neo4j graph database, with plenty of Cypher examples.
Explore: artificial intelligence • community detection algorithm • deep learning • DeepWalk • graph algorithms • Graph Analytics • graph database • graph embeddings • java • machine learning
AI & Graph Technology: AI Explainability
By David Penick
August 26, 2019 3 mins read
Read the fifth and final installment of our blog series on artificial intelligence and the ways AI explainability adds context for credibility.
Explore: AI / Machine Learning • blog • graph database • Graph Databases • graph platform • graph technology • Knowledge Graph • machine learning • neo4j
AI & Graph Technology: Connections Improve Accuracy
By David Penick
August 19, 2019 2 mins read
Read the fourth installment of this blog series on artificial intelligence on the ways connected feature extraction analyzes data.
Explore: AI / Machine Learning • connected features • graph algorithms • Graph Analytics • graph database • graph platform • Knowledge Graph • machine learning • neo4j • Neo4j Graph Platform
Visualizing This Week in Tech
By Jocelyn Hoppa
August 15, 2019 6 mins read
Learn how to visualize common elements amongst the barrage of weekly tech stories with knowledge graphs and machine learning techniques.
Explore: ai • cypher • Data Visualization • Doc2Vec • graph algorithms • graph model • Knowledge Graph • machine learning • Named Entity Recognition • natural language understanding
AI & Graph Technology: What Are Knowledge Graphs?
By David Penick
August 5, 2019 4 mins read
Read the second installment of this blog series on artificial intelligence on the ways knowledge graphs add context for decision support.
Explore: AI / Machine Learning • artificial intelligence • Graph Algorithm • graph algorithms • graph database • graph technology • Knowledge Graph • machine learning • natural language processing • neo4j
AI and Graph Technology: 4 Ways Graphs Add Context
By David Penick
July 29, 2019 5 mins read
Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.
Explore: ai • AI explainability • artificial intelligence • deep learning • graph algorithms • graph database • Graph Databases • graph technology • knowledge graphs • machine learning
Toward AI Standards: Context Makes AI More Reliable and Trustworthy
By Jocelyn Hoppa
July 22, 2019 6 mins read
Discover why native graph technology is the key to making artificial intelligence and machine learning more reliable and trustworthy.
Explore: AI solutions • AI standards • contextual information • corporate fraud • data lineage • GDPR • graph technology • Knowledge Graph • machine learning • native graph
Graphs in Banking: Integration with AI & Machine Learning [Video]
By Allison Wu
July 16, 2019 < 1 min read
Check out this webinar on graph technology within the financial services industry, featuring use cases on fraud detection, MDM and IAM.
Explore: ai • banking • financial services • fraud • graph database • iam • machine learning • Master Data Management • MDM • webinar
Toward AI Standards: Context Makes AI More Robust
By Jocelyn Hoppa
July 15, 2019 4 mins read
Read this third blog in our series “Toward AI Standards” and discover how graph technology adds context to data relationships for more robust AI solutions.
Explore: ai • AI application • AI solution • Boeing • chatbot • Data Relationships • fraud detection • graph algorithms • graph analysis • graph platform
Deciphering Product DNA: Next-Level PDM with AI & Knowledge Graphs
By Jocelyn Hoppa
July 9, 2019 4 mins read
Increasingly complex products undoubtedly require greater management of components, function and data. Classic product data management (PDM) has long reach its limits in this respect. Breaking down product DNA is now driven by artificial intelligence (AI) and knowledge graphs. In… Read more →
Explore: ai • artificial intelligence • bill of materials • ERP • knowledge graphs • machine learning • manufacturers • natural language processing • pdm • PIM
Liberating Knowledge: Machine Learning Techniques with Neo4j
By Jocelyn Hoppa
July 3, 2019 13 mins read
Explore how Hume leverages natural language understanding, graph analytics and AI capabilities to connect data and share knowledge.
Explore: ai • Connected Data • Graph Analytics • graph-based search • graphconnect • Hume • Knowledge Graph • machine learning • natural language understanding • neo4j
Toward AI Standards: Graph Technology for Responsible AI
By Jocelyn Hoppa
July 2, 2019 3 mins read
Read the first installment of this four-part series on how graphs provide the context artificial intellingence needs to remain reliable and trustworthy.
Explore: AI applications • AI solutions • Amazon • artificial intelligence • contextual information • decision path • graph platforms • graph technology • machine learning • twitter
Graphs in Automotive & Manufacturing: Unlock New Value from Your Data [Video]
By Allison Wu
June 27, 2019 < 1 min read
Check out this webinar on using graph database technology in the manufacturing and automotive industries, including the use of graph algorithms in AI.
Explore: ai • artificial intelligence • automotive • bill of materials • graph algorithms • logistics • machine learning • manufacturing • supply chain management • webinar
Toward AI Standards: Why Context Is Critical for Artificial Intelligence
By Bryce Merkl Sasaki
June 24, 2019 3 mins read
Learn what Neo4j CEO Emil Eifrem believes is the most critical component of both technical and ethical standards for AI – and how we might make it happen.
Explore: ai • AI standards • artificial intelligence • graph technology • Knowledge Graph • logic processing • machine learning • National Institute of Standards and Technology • NIST • Panama Papers
